Neuroprotective treatment for Parkinson's disease (PD) has become a reality. In order to maximize the benefits of clinical neuroprotection, therapies should be applied as early as possible and even before the clinical diagnosis of PD. Therefore, proper identification of patients in the earliest stages of the disease is a priority. The key to effective secondary prevention trials is identifying valid and reliable biomarkers that confidently reflect the preclinical trait of PD. Measures of dopamine nerve terminal integrity with positron emission tomography (PET) have allowed preclinical disease to be detected in relatives of patients with PD. As screening the whole population for preclinical PD using PET is not cost-effective, there is a clear need for screening methods to identify subjects who are at a high risk for this disease. A biomarker, to be useful in screening large populations to identify very early disease, should be inexpensive, easily administered, and sufficiently sensitive and specific to avoid unacceptable false negatives or positives. Since a single test may not have sufficient specificity or sensitivity to detect very early disease, a multitiered approach may be required. In such a scheme, a battery of tests that is easily administered, inexpensive and sensitive (although not highly specific) would represent the first screening tier to select at risk individuals who then undergo increasingly more sophisticated tests of higher specificity. As a number of motor and non-motor manifestations of the disease emerge months to years before a diagnosis can be made, a battery of clinicometric tests might be able to identify individuals at a subclinical stage of PD. The overarching goal of this project is to propose a multitiered approach to the diagnosis of preclinical or prodromal PD using risk factor-based subject recruitment (family history), postural motor system and formalized clinicometric PD test battery screening to identify minimally symptomatic subjects. Dopaminergic (11C-beta-CFT) brain PET imaging will be used as the gold standard for the diagnosis of very early PD in subjects with abnormal screening results. We will validate the different components of the clinicometric and posturographic test battery as possible biomarkers by defining their in vivo dopaminergic PET correlations in patients with PD (symptom -> PET). As normal aging is also associated with dopaminergic neuronal loss (but in a different striatal pattern), we will more clearly define the clinical specificity of abnormal screening results by comparing the clinical profile associated with a PET-based topographic pattern of PD to that of age-associated striatal dopaminergic denervation (PET -> symptom).